An electronic media platform provides access to media data (e.g., electronic content). A user operates a computing device to remotely connect to the electronic media platform and request particular media data (e.g., a media file). The requested media data is sent to the computing device for presentation to the user.
The media data can include audio data, video data, and/or other multimedia data. In many situations, storing the media data in its original format uses a relatively large storage space, and transmitting the media data in its original format uses a relatively large network bandwidth. To reduce these storage space and network bandwidth requirements, the electronic media platform implements data compression, such as a codec that uses vector quantization.
Data compression techniques often cause latency when accessing the media data. One reason for the latency is because the data compression involves computationally complex operations to transform the media data from the original format to the compressed format. Furthermore, an increase in the user demand and/or a decrease in the availability of the computing resources worsens the latency.
To reduce latency, many existing electronic media platforms adjust the available computing resources by, for example, adding or removing resources. Such existing platforms operate in a reactive mode or in a proactive mode. In the reactive mode, an electronic media platform adjusts the computing resources, but only after a latency degradation is observed. However, in this mode, the performance of the electronic media platform is not improved until the adjustment is completed. In the proactive mode, an electronic media platform typically predicts the user demand and adjusts the computing resources beforehand. However in this mode, the performance enhancement does not account for unforeseen fluctuations in the user demand or the availability of the computing resources. Hence, the performance may still not be the optimal performance. For example, if the actual demand is greater than the predicted use demand, the computing resources are over-committed because the adjustment fails to deploy enough computing resources. Conversely, if the actual demand is relatively smaller, the computing resources are under-committed because the adjustment deploys unnecessary computing resources. Further, if there is a resource failure (e.g., a set of computing resources goes offline), the electronic media platform has to revert back to the reactive mode.